The conodont species Caenodontus serrulatus Behnken is a rare coniform element first described in 1975 from Guadalupian strata exposed in the Guadalupe and Delaware Mountains of West Texas. Because it is rare, coniform, and occurs long after most coniform elements supposedly disappeared, it has been hauntingly mysterious. Based on new material containing a varied assemblage of coniform elements recovered from an outcrop of the Hegler Limestone (Guadalupian) in the Patterson Hills, West Texas, it is proposed that Caenodontusis comprised of a 6-7 membrate coniform apparatus and that this apparatus is very similar to the one proposed for the genus Ansella from the Ordovician.
","language":"English","publisher":"Micropaleontology Press","usgsCitation":"Nestell, M.K., and Wardlaw, B.R., 2015, An apparatus reconstruction of the conodont Caenodontus serrulatus Behnken 1975: Micropaleontology, v. v. 61, no. no 4 - 5, p. 293-300.","productDescription":"7 p.","startPage":"293","endPage":"300","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071098","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":325706,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":325705,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.micropress.org.ezproxy.library.wisc.edu/microaccess/micropaleontology"}],"country":"United States","state":"Texas","otherGeospatial":"Guadalupe Mountains National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.95582580566406,\n 31.997012406423654\n ],\n [\n -104.95719909667969,\n 31.98187064456415\n ],\n [\n -104.95719909667969,\n 31.974881296156596\n ],\n [\n -104.95994567871094,\n 31.970803930433096\n ],\n [\n -104.96131896972656,\n 31.959153316146658\n ],\n [\n -105.00251770019531,\n 31.956240431596452\n ],\n [\n -105.01350402832031,\n 31.955657843600374\n ],\n [\n -105.01350402832031,\n 31.946918580249633\n ],\n [\n -105.02792358398436,\n 31.944587969619008\n ],\n [\n -105.03067016601562,\n 31.893299584369487\n ],\n [\n -105.02792358398436,\n 31.875808372704054\n ],\n [\n -105.00595092773438,\n 31.868227816180674\n ],\n [\n -104.99977111816406,\n 31.87056036152958\n ],\n [\n -104.9908447265625,\n 31.85598098460412\n ],\n [\n -104.95788574218749,\n 31.853648070322752\n ],\n [\n -104.95101928710938,\n 31.87172661206501\n ],\n [\n -104.93453979492186,\n 31.868810958052563\n ],\n [\n -104.92973327636719,\n 31.85073184447357\n ],\n [\n -104.92218017578125,\n 31.828565514766165\n ],\n [\n -104.92424011230469,\n 31.808144448024276\n ],\n [\n -104.87136840820312,\n 31.798807599289702\n ],\n [\n -104.83360290527342,\n 31.81572994283835\n ],\n [\n -104.8370361328125,\n 31.85073184447357\n ],\n [\n -104.82536315917967,\n 31.86064663609563\n ],\n [\n -104.80957031249999,\n 31.876974556818304\n ],\n [\n -104.79583740234375,\n 31.88105608497267\n ],\n [\n -104.77935791015625,\n 31.886886525780806\n ],\n [\n -104.75875854492188,\n 31.904375633517787\n ],\n [\n -104.76493835449219,\n 31.92885480180959\n ],\n [\n -104.76356506347655,\n 31.943422642136195\n ],\n [\n -104.73541259765625,\n 31.951579624162896\n ],\n [\n -104.72442626953124,\n 31.974298826428072\n ],\n [\n -104.72511291503906,\n 31.992353668990656\n ],\n [\n -104.72648620605469,\n 31.99992399713997\n ],\n [\n -104.95582580566406,\n 31.997012406423654\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"v. 61","issue":"no 4 - 5","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5799db32e4b0589fa1c7e693","contributors":{"authors":[{"text":"Nestell, Merlynd K.","contributorId":68603,"corporation":false,"usgs":false,"family":"Nestell","given":"Merlynd","email":"","middleInitial":"K.","affiliations":[{"id":12734,"text":"University of Texas at Arlington","active":true,"usgs":false}],"preferred":false,"id":643492,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wardlaw, Bruce R. bwardlaw@usgs.gov","contributorId":266,"corporation":false,"usgs":true,"family":"Wardlaw","given":"Bruce","email":"bwardlaw@usgs.gov","middleInitial":"R.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":643491,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70159801,"text":"ds973 - 2015 - Chemical concentrations and instantaneous loads, Green River to the Lower Duwamish Waterway near Seattle, Washington, 2013–15","interactions":[],"lastModifiedDate":"2015-12-28T12:34:29","indexId":"ds973","displayToPublicDate":"2015-12-23T10:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"973","title":"Chemical concentrations and instantaneous loads, Green River to the Lower Duwamish Waterway near Seattle, Washington, 2013–15","docAbstract":"In November 2013, U.S. Geological Survey streamgaging equipment was installed at a historical water-quality station on the Duwamish River, Washington, within the tidal influence at river kilometer 16.7 (U.S. Geological Survey site 12113390; Duwamish River at Golf Course at Tukwila, WA). Publicly available, real-time continuous data includes river streamflow, stream velocity, and turbidity. Between November 2013 and March 2015, the U.S. Geological Survey collected representative samples of water, suspended sediment, or bed sediment from the streamgaging station during 28 periods of differing flow conditions. Samples were analyzed by Washington-State-accredited laboratories for a large suite of compounds, including metals, dioxins/furans, semivolatile compounds including polycyclic aromatic hydrocarbons, pesticides, butytins, polychlorinated biphenyl (PCB) Aroclors and the 209 PCB congeners, volatile organic compounds, hexavalent chromium, and total and dissolved organic carbon. Metals, PCB congeners, and dioxins/furans were frequently detected in unfiltered-water samples, and concentrations typically increased with increasing suspended-sediment concentrations. Chemical concentrations in suspendedsediment samples were variable between sampling periods. The highest concentrations of many chemicals in suspended sediment were measured during summer and early autumn storm periods.
\nMedian chemical concentrations in suspended-sediment samples were greater than median chemical concentrations in fine bed sediment (less than 62.5 µm) samples, which were greater than median chemical concentrations in paired bulk bed sediment (less than 2 mm) samples. Suspended-sediment concentration, sediment particle-size distribution, and general water-quality parameters were measured concurrent with the chemistry sampling. From this discrete data, combined with the continuous streamflow record, estimates of instantaneous sediment and chemical loads from the Green River to the Lower Duwamish Waterway were calculated. For most compounds, loads were higher during storms than during baseline conditions because of high streamflow and high chemical concentrations. The highest loads occurred during dam releases (periods when stored runoff from a prior storm is released from the Howard Hanson Dam into the upper Green River) because of the high river streamflow and high suspended-sediment concentration, even when chemical concentrations were lower than concentrations measured during storm events.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds973","collaboration":"Prepared in cooperation with the Washington State Department of Ecology","usgsCitation":"Conn, K.E., Black, R.W., Vanderpool-Kimura, A.M., Foreman, J.R., Peterson, N.T., Senter, C.A., and Sissel, S.K., 2015, Chemical concentrations and instantaneous loads, Green River to the Lower Duwamish Waterway near Seattle, Washington, 2013–15: U.S. Geological Survey Data Series 973, 46 p., https://dx.doi.org/10.3133/ds973.","productDescription":"Report: vii, 46 p.; Appendix","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-065963","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":312810,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0973/ds973.pdf","text":"Report","size":"2.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 973 PDF"},{"id":312811,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/0973/coverthb.jpg"},{"id":312812,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/0973/ds973_appendixa.xlsx","text":"Appendix A","size":"846 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"DS 973 Appendix A XLSX"}],"country":"United States","state":"Washington","otherGeospatial":"Green River, Lower Duwamish Waterway","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.4,\n 47.4\n ],\n [\n -122.4,\n 47.6\n ],\n [\n -122.2,\n 47.6\n ],\n [\n -122.2,\n 47.4\n ],\n [\n -122.4,\n 47.4\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Washington Water Science Center
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The hydrogeology of the Owego-Apalachin Elementary School geothermal fields, which penetrate saline water and methane in fractured upper Devonian age bedrock in the Owego Creek valley, south-central New York, was characterized through the analysis of drilling and geophysical logs, water-level monitoring data, and specific-depth water samples. Hydrogeologic insights gained during the study proved beneficial for the design of the geothermal drilling program and protection of the overlying aquifer during construction, and may be useful for the development of future geothermal fields and other energy-related activities, such as drilling for oil and natural gas in similar fractured-bedrock settings.
\nThe southwest geothermal field consists of 204 closed-loop wells that penetrate a major saline water-bearing zone associated with bedding-plane fractures near the middle of an interbedded sandstone and shale interval at depths of 238 to 263 feet below land surface (ft bls). The northeast geothermal field consists of 80 closed-loop wells that penetrate a major saline water-bearing zone associated with bedding-plane fractures near the base of the interbedded sandstone and shale interval at depths of 303 to 323 ft bls.
\nTransmissivity estimates for the major saline water-bearing fractured zones range from 735 to 3,400 feet squared per day. The saline water-bearing zone in the southwest field is hydraulically connected over a horizontal distance of at least 350 feet. The hydraulic connection between subhorizontal, stacked bedding-plane fractures is limited by the number and transmissivity of interspersed higher angle fractures; locally, greater stratigraphic separation results in reduced connectivity to a greater degree than does horizontal distance.
\nThe specific conductance of the saline water from the shallower fractured zone in the southwest field was about 16,000 microsiemens per centimeter at 25 degrees Celsius (μS/cm at 25°C), and that from the fractured zone in the northeast field was about 65,000 μS/cm at 25°C. The saline waters were characterized by a chemical composition similar to that of deep formation brines collected from oil and gas wells in the Appalachian Basin. About 40 percent of the geothermal wells discharged methane gas to land surface during and (or) following drilling. Sandstone beds at depths of 348 to 378 ft bls are the likely source of the methane gas, which was determined to be early thermogenic in origin.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155155","usgsCitation":"Williams, J.H., and Kappel, W.M., 2015, Hydrogeology of the Owego-Apalachin Elementary School geothermal fields, Tioga County, New York: U.S. Geological Survey Scientific Investigations Report 2015–5155, 29 p., https://dx.doi.org/10.3133/sir20155155.","productDescription":"Report: vii, 29 p.; 4 Appendixes","numberOfPages":"29","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-066669","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":312655,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5155/sir20155155_appendix02.xlsx","text":"Appendix 2","size":"23 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2015-5155","linkHelpText":"Location, construction, and hydrogeologic information for selected boreholes and wells"},{"id":312729,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5155/sir20155155_appendix01.m4v","text":"Appendix 1 (Low Resolution)","size":"5.12 MB","description":"SIR 2015-5155","linkHelpText":"Video of local news report about methane fire during drilling of borehole A9"},{"id":312730,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5155/sir20155155_appendix04.m4v","text":"Appendix 4 (Low Resolution)","size":"35.6 MB","description":"SIR 2015-5155","linkHelpText":"Video of unloading of methane gas and water from borehole A12"},{"id":312654,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5155/sir20155155_appendix01.mp4","text":"Appendix 1 (High Resolution)","size":"10.2 MB","description":"SIR 2015-5155","linkHelpText":"Video of local news report about methane fire during drilling of borehole A9"},{"id":312657,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5155/sir20155155_appendix04.mp4","text":"Appendix 4 (High Resolution)","size":"49.8 MB","description":"SIR 2015-5155","linkHelpText":"Video of unloading of methane gas and water from borehole A12"},{"id":312652,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5155/sir20155155.pdf","text":"Report","size":"7.60 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5155"},{"id":312651,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5155/images/coverthb.jpg"},{"id":312656,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5155/sir20155155_appendix03.xlsx","text":"Appendix 3","size":"15 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2015-5155","linkHelpText":"Field and laboratory chemical analyses from boreholes A9 and Q1"}],"country":"United States","state":"New York","county":"Tioga County","city":"Owego","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-76.1258,42.4107],[-76.123,42.3825],[-76.1267,42.382],[-76.1247,42.3652],[-76.1173,42.3653],[-76.1172,42.3576],[-76.1129,42.3571],[-76.1122,42.348],[-76.1084,42.3476],[-76.1071,42.3376],[-76.1195,42.3375],[-76.1194,42.3275],[-76.1139,42.3276],[-76.1144,42.3185],[-76.1069,42.3181],[-76.1069,42.3094],[-76.1025,42.309],[-76.1031,42.3026],[-76.0981,42.3022],[-76.0993,42.2927],[-76.1073,42.2931],[-76.1079,42.2876],[-76.1017,42.2877],[-76.1023,42.2808],[-76.088,42.2804],[-76.0892,42.275],[-76.0842,42.2746],[-76.0842,42.2664],[-76.0798,42.2659],[-76.0791,42.2587],[-76.0965,42.2595],[-76.0964,42.25],[-76.0909,42.25],[-76.0921,42.2459],[-76.0859,42.2459],[-76.0858,42.2414],[-76.092,42.2414],[-76.0913,42.2337],[-76.0845,42.2341],[-76.0857,42.2282],[-76.082,42.2273],[-76.0801,42.2183],[-76.0862,42.2178],[-76.085,42.2119],[-76.0912,42.2123],[-76.0899,42.2064],[-76.083,42.2069],[-76.0823,42.1928],[-76.0885,42.1928],[-76.0885,42.1869],[-76.1151,42.1858],[-76.1123,42.1509],[-76.106,41.9991],[-76.1165,41.9992],[-76.1467,41.9991],[-76.3826,41.9989],[-76.466,41.9999],[-76.5229,42.0005],[-76.5531,42.0008],[-76.5618,42.0009],[-76.5675,42.0121],[-76.5632,42.0153],[-76.544,42.0536],[-76.5538,42.0885],[-76.5581,42.1239],[-76.5594,42.1312],[-76.5539,42.1312],[-76.5597,42.1507],[-76.5598,42.1557],[-76.5344,42.1568],[-76.5377,42.2504],[-76.5382,42.2817],[-76.4731,42.2808],[-76.4734,42.2631],[-76.417,42.2631],[-76.4153,42.3194],[-76.3507,42.3181],[-76.35,42.3085],[-76.2898,42.308],[-76.2891,42.2962],[-76.25,42.2964],[-76.2514,42.3073],[-76.2497,42.3241],[-76.2473,42.336],[-76.2425,42.3446],[-76.2382,42.3542],[-76.2402,42.3624],[-76.2433,42.3664],[-76.2764,42.3794],[-76.2944,42.3816],[-76.2957,42.3866],[-76.2947,42.4075],[-76.2549,42.4082],[-76.1258,42.4107]]]},\"properties\":{\"name\":\"Tioga\",\"state\":\"NY\"}}]}","contact":"Director, New York Water Science Center
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425 Jordan Road
Troy, NY 12180-8349
Federal agencies that oversee land management for much of the Snake Range in eastern Nevada, including the management of Great Basin National Park by the National Park Service, need to understand the potential extent of adverse effects to federally managed lands from nearby groundwater development. As a result, this study was developed (1) to attain a better understanding of aquifers controlling groundwater flow on the eastern side of the southern part of the Snake Range and their connection with aquifers in the valleys, (2) to evaluate the relation between surface water and groundwater along the piedmont slopes, (3) to evaluate sources for Big Springs and Rowland Spring, and (4) to assess groundwater flow from southern Spring Valley into northern Hamlin Valley. The study focused on two areas—the first, a northern area along the east side of Great Basin National Park that included Baker, Lehman, and Snake Creeks, and a second southern area that is the potential source area for Big Springs. Data collected specifically for this study included the following: (1) geologic field mapping; (2) drilling, testing, and water quality sampling from 7 test wells; (3) measuring discharge and water chemistry of selected creeks and springs; (4) measuring streambed hydraulic gradients and seepage rates from 18 shallow piezometers installed into the creeks; and (5) monitoring stream temperature along selected reaches to identify places of groundwater inflow.
\nThe Snake Range was formed by a generally normal-faulted uplift, where late Proterozoic and Cambrian siliciclastic rocks and metamorphic rocks are present at the highest altitudes and younger Paleozoic carbonate rocks are exposed along the flanks. The consolidated rocks are intruded by Jurassic to Tertiary age plutons, which are most common between the Lehman and Snake Creek drainage basins. Older Cenozoic rocks, including Oligocene volcanic rocks and Miocene sedimentary rocks, crop out locally and fill the basins that underlie Snake, Spring, and Hamlin Valleys. Younger Tertiary and Quaternary sedimentary (basin-fill) deposits overlie the older Cenozoic rocks.
\nThe rocks and deposits can be divided into three distinct aquifers. These aquifers include (1) basin-fill aquifers that consist of the permeable parts of the Cenozoic basin fill and some fractured or jointed Cenozoic volcanic rocks, (2) an upper carbonate-rock aquifer that consists of upper Paleozoic carbonate rocks overlying a regionally extensive middle Paleozoic siliciclastic confining unit, and (3) a lower carbonate-rock aquifer that consists of lower Paleozoic carbonate rocks. Secondary openings created by faults, shear zones, fractures, and, in the carbonate rocks, karst solution features, largely determine the water-transmitting properties of the volcanic- and carbonate-rock aquifers. The basin-fill aquifers are composed of a wide variety of rock types and have highly variable hydraulic properties. The three aquifers are stratigraphically and structurally heterogeneous, causing large variations in the ability to store and transmit water. The aquifers are separated by confining units in some areas and are in contact with each other in other areas, yet function as a single, composite aquifer system. Basin-fill aquifers most often overlie or adjoin the lower and upper carbonate-rock aquifers.
\nBaker, Lehman and Snake Creek drainage basins were divided into five hydrologic zones on the basis of climate, geology, and topography. The five zones, from highest to lowest altitudes, are the mountain-upland, karst-limestone, upper-piedmont, lower-piedmont, and valley-lowland zones. The primary hydrologic connection between the mountain-upland and the valley-lowland zones is streamflow. Much of the streamflow from the mountain-upland zone is generated above tree line.
\nGroundwater flow increases in the karst-limestone zone because of increased permeability caused by dissolution, which results in increased streamflow losses. Most of the increased groundwater flow is to springs near faults that form the boundary with the upper-piedmont zone. Thus, groundwater flow from the karst-limestone zone to the upper-piedmont zone was only 10 percent of the combined flow of streams and springs that exit the karst-limestone zone. About 60 percent of the water flowing from Rowland Spring in the Lehman Creek drainage basin was from streamflow losses along Baker Creek. The remaining flow from Rowland Spring comes from local recharge in the karst-limestone zone.
\nIn the upper-piedmont zone, the water table by Baker, Lehman and Snake Creeks was near the water level in the creeks for several hundred feet downstream from the karst-limestone zone. Water levels in piezometers along Snake Creek downstream from its confluence with Spring Creek were far below the streambed, indicating gravity drainage beneath this section of the creek. Estimated vertical hydraulic conductivity along a 3-mile reach of Snake Creek downstream of this confluence was 0.5 foot per day, which was an order of magnitude less than that estimated for Baker and Lehman Creeks. The low vertical hydraulic conductivity in the streambed along the lower reaches of Snake Creek results from chemical precipitation of calcite caused by off-gassing of carbon dioxide derived from springs at the end of the karst-limestone zone.
\nThe younger alluvial deposits thicken rapidly across faults that form the upper boundary of the lower-piedmont zone. The absence of springs or groundwater flow to the creeks upstream of these faults indicates they are not a complete barrier to groundwater flow. The water table was shallow in the valley-lowland zone in the Baker and Lehman Creek drainage basins, whereas the water table was more than 50 feet below land surface in the Snake Creek drainage basin. In contrast to thick basin fill in the valley-lowland zone in the Baker and Lehman Creek drainage basins, fractured and karst limestone underlie basin fill at relatively shallow depths in Snake Creek drainage basin. The underlying limestone acts as a drain for groundwater in the basin fill beneath Snake Creek.
\nA groundwater divide in southern Spring Valley south of Baking Powder Flat separates groundwater flow to the flat from southeastward flow into northern Hamlin Valley. Groundwater flow from southern Spring Valley south of the groundwater divide into northern Hamlin Valley was estimated to range from 6,000 to 11,000 acre-feet per year. This groundwater does not flow to Big Springs in southern Snake Valley; rather, the source of water to Big Springs is groundwater recharge in the Big Spring Wash drainage basin and in nearby smaller drainage basins at the south end of the Snake Range.
\nGroundwater flow from southern Spring Valley continues through the western side of Hamlin Valley before being directed northeast toward the south end of Snake Valley. This flow is constrained by southward-flowing groundwater from Big Spring Wash and northward-flowing groundwater beneath central Hamlin Valley. The redirection to the northeast corresponds to a narrowing of the width of flow in southern Snake Valley caused by a constriction formed by a steeply dipping middle Paleozoic siliciclastic confining unit exposed in the flanks of the mountains and hills on the east side of southern Snake Valley and shallowly buried beneath basin fill in the valley. The narrowing of groundwater flow could be responsible for the large area where groundwater flows to springs or is lost to evapotranspiration between Big Springs in Nevada and Pruess Lake in Utah.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1819","collaboration":"Prepared in cooperation with the National Park Service, Bureau of Land Management, U.S. Fish and Wildlife Service, and U.S. Forest Service","usgsCitation":"Prudic, D.E, Sweetkind, D.S., Jackson, T.R., Dotson, K.E., Plume, R.W., Hatch, C.E., and Halford, K.J. 2015, Evaluating connection of aquifers to springs and streams, Great Basin National Park and vicinity, Nevada: U.S. Geological Survey Professional Paper 1819, 188 p., https://dx.doi.org/10.3133/pp1819.","productDescription":"Report: xxii, 187 p.; Appendixes 1-16","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-034324","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":312322,"rank":16,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/pp/1819/pp1819_appendix14.zip","text":"Appendix 14","size":"4.3 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Nevada Water Science Center
U.S. Geological Survey
2730 N. Deer Run Rd.
Carson City, NV 89701
http://nevada.usgs.gov/water/
Benthic invertebrate communities are monitored because the composition of those communities can effect and be affected by the water quality of an aquatic system. Benthic communities use and sometimes regulate the cycling of essential elements (for example, carbon). Benthic invertebrate taxa may also indicate acutely and chronically stressful environments because they are mostly sessile, accumulate contaminants, and sometimes respond dramatically to oligotrophic as well as eutrophic conditions. Benthic communities can in turn affect water quality by grazing pelagic food resources and increasing the rate of nutrient regeneration through feeding and bioturbating the sediment.
South San Francisco Bay is a system dependent on phytoplankton as the base to the food web. Despite abundant nutrients, south San Francisco Bay has had limited phytoplankton production in the last several decades owning to poor light conditions and high grazing losses from the water column by benthic invertebrates. The south San Francisco Bay achieves a balance of biogeochemical conditions in most springs to accommodate a short phytoplankton bloom. This balance has maintained the phytoplankton in south San Francisco Bay at low biomass levels relative to other high-nutrient urban estuaries. The role that benthic invertebrates play in this balance, in these episodic spring events, and in other seasons within the estuary remains of great interest to water-quality and biological resource managers.
Our primary objective in this study is to quantify current (2014) benthic-community structure and function in the south San Francisco Bay sloughs and to compare those communities temporally over decadal time scales with a unique long-term dataset. The study area (fig. 1) is inclusive of the area south of the Dumbarton Bridge (DB) including Alviso and Guadalupe Sloughs and Coyote Creek.
The following are results highlighted in this report:
NRP staff, National Research Program
U.S. Geological Survey
345 Middlefield Road, MS-435
Menlo Park, CA 94025
http://water.usgs.gov/nrp/
Georges Bank is a shallow submarine bank that lies south of Nova Scotia and east of Cape Cod and bounds the seaward side of the Gulf of Maine. The international boundary between Canada and the United States transects the bank, and the eastern part of the bank (~7500 square kilometres) lies in Canadian territory. This map shows the surficial geology of a part of Georges Bank at a scale of 1:50 000. This map has companion topographic and backscatter strength maps. These companion maps provide a basis for interpreting the origin of seafloor features and the nature of materials that form the seafloor. The maps are based on multibeam-sonar surveys conducted in 1999 and 2000 to map 11,965 square kilometres of the seafloor.
","largerWorkTitle":"Geological Survey of Canada Open File series","language":"English","publisher":"Natural Resources Canada","doi":"10.4095/296975","usgsCitation":"Todd, B., and Valentine, P.C., 2015, Surficial geology and shaded seafloor relief of Georges Bank, Fundian Channel and Northeast Channel, Gulf of Maine, https://doi.org/10.4095/296975.","ipdsId":"IP-065278","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":471558,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.4095/296975","text":"Publisher Index Page"},{"id":337559,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":328897,"type":{"id":15,"text":"Index Page"},"url":"https://dx.doi.org/10.4095/296975"}],"publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58c90127e4b0849ce97abcef","contributors":{"authors":[{"text":"Todd, B.J.","contributorId":120970,"corporation":false,"usgs":false,"family":"Todd","given":"B.J.","email":"","affiliations":[],"preferred":false,"id":649436,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Valentine, Page C. 0000-0002-0485-6266 pvalentine@usgs.gov","orcid":"https://orcid.org/0000-0002-0485-6266","contributorId":1947,"corporation":false,"usgs":true,"family":"Valentine","given":"Page","email":"pvalentine@usgs.gov","middleInitial":"C.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":649435,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70159884,"text":"sir20155122 - 2015 - Estimating natural recharge in San Gorgonio Pass watersheds, California, 1913–2012","interactions":[],"lastModifiedDate":"2019-12-30T14:34:52","indexId":"sir20155122","displayToPublicDate":"2015-12-21T19:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-5122","title":"Estimating natural recharge in San Gorgonio Pass watersheds, California, 1913–2012","docAbstract":"A daily precipitation-runoff model was developed to estimate spatially and temporally distributed recharge for groundwater basins in the San Gorgonio Pass area, southern California. The recharge estimates are needed to define transient boundary conditions for a groundwater-flow model being developed to evaluate the effects of pumping and climate on the long-term availability of groundwater. The area defined for estimating recharge is referred to as the San Gorgonio Pass watershed model (SGPWM) and includes three watersheds: San Timoteo Creek, Potrero Creek, and San Gorgonio River. The SGPWM was developed by using the U.S. Geological Survey INFILtration version 3.0 (INFILv3) model code used in previous studies of recharge in the southern California region, including the San Gorgonio Pass area. The SGPWM uses a 150-meter gridded discretization of the area of interest in order to account for spatial variability in climate and watershed characteristics. The high degree of spatial variability in climate and watershed characteristics in the San Gorgonio Pass area is caused, in part, by the high relief and rugged topography of the area.
\nDaily climate data developed from a network of monitoring sites and published average monthly precipitation maps were used to develop the climate inputs for the SGPWM. Geographic Information System (GIS) data defining land surface altitude, vegetation, soils, surficial geology, and land cover were used to define input parameters representing the physical characteristics of the land surface, root zone, and shallow subsurface underlying the root zone. Model parameterization was based on a previous INFILv3 model developed for an area including the upper parts of the San Timoteo Creek and Potrero Creek drainages and the western part of the San Gorgonio River watershed. The previous INFILv3 model was calibrated by using available streamflow records from the model area. The SGPWM uses an updated INFILv3 version to represent shallow groundwater flow better beneath the root zone that contributes to lateral, downslope seepage rather than deep recharge. The SGPWM calibration was tested by using available streamflow records in the San Gorgonio Pass region.
\nThe SGPWM was used to simulate a 100-year water budget, including recharge and runoff, for water years 1913 through 2012. Results indicated that most recharge came from episodic infiltration of surface-water runoff in the larger stream channels. Results also indicated periods of great variability in recharge and runoff in response to variability in precipitation. More recharge was simulated for the area of the groundwater basin underlying the more permeable alluvial fill of the valley floor compared to recharge in the neighboring upland areas of the less permeable mountain blocks. The greater recharge was in response to the episodic streamflow that discharged from the mountain block areas and quickly infiltrated the permeable alluvial fill of the groundwater basin. Although precipitation at the higher altitudes of the mountain block was more than double precipitation at the lower altitudes of the valley floor, recharge for inter-channel areas of the mountain block was limited by the lower permeability bedrock underlying the thin soil cover, and most of the recharge in the mountain block was limited to the main stream channels underlain by alluvial fill.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155122","collaboration":"Prepared in cooperation with the San Gorgonio Pass Water Agency","usgsCitation":"Hevesi, J.A., and Christensen, A.H., 2015, Estimating natural recharge in San Gorgonio Pass watersheds, California, 1913–2012: U.S. Geological Survey Scientific Investigations Report 2015–5122, 74 p. https://dx.doi.org/10.3133/ SIR20155122.","productDescription":"xii, 74 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-054946","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":312622,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5122/sir20155122.pdf","text":"Report","size":"29.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5122"},{"id":312621,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5122/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Gorgonio Pass","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.301025390625,\n 33.43831750748322\n ],\n [\n -116.05682373046875,\n 33.43831750748322\n ],\n [\n -116.05682373046875,\n 34.19135773925218\n ],\n [\n -117.301025390625,\n 34.19135773925218\n ],\n [\n -117.301025390625,\n 33.43831750748322\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, CA 95819
http://ca.water.usgs.gov
Bat mortality rates from white-nose syndrome and wind power development are unprecedented. Cryptic and wide-ranging behaviours of bats make them difficult to survey, and population estimation is often intractable. We advance a model-based framework for making spatially explicit predictions about summertime distributions of bats from capture and acoustic surveys. Motivated by species-energy and life-history theory, our models describe hypotheses about spatio-temporal variation in bat distributions along environmental gradients and life-history attributes, providing a statistical basis for conservation decision-making.
\nOregon and Washington, USA.
\nWe developed Bayesian hierarchical models for 14 bat species from an 8-year monitoring dataset across a ~430,000 km2 study area. Models accounted for imperfect detection and were temporally dynamic. We mapped predicted occurrence probabilities and prediction uncertainties as baselines for assessing future declines.
\nForest cover, snag abundance and cliffs were important predictors for most species. Species occurrence patterns varied along elevation and precipitation gradients, suggesting a potential hump-shaped diversity–productivity relationship. Annual turnover in occurrence was generally low, and occurrence probabilities were stable among most species. We found modest evidence that turnover covaried with the relative riskiness of bat roosting and migration. The fringed myotis (Myotis thysanodes), canyon bat (Parastrellus hesperus) and pallid bat (Antrozous pallidus) were rare; fringed myotis occurrence probabilities declined over the study period. We simulated anticipated declines to demonstrate that mapped occurrence probabilities, updated over time, provide an intuitive way to assess bat conservation status for a broad audience.
\nLandscape keystone structures associated with roosting habitat emerged as regionally important predictors of bat distributions. The challenges of bat monitoring have constrained previous species distribution modelling efforts to temporally static presence-only approaches. Our approach extends to broader spatial and temporal scales than has been possible in the past for bats, making a substantial increase in capacity for bat conservation.
","language":"English","publisher":"Blackwell Science","publisherLocation":"Oxford","doi":"10.1111/ddi.12372","usgsCitation":"Rodhouse, T., Ormsbee, P., Irvine, K.M., Vierling, L.A., Szewczak, J.M., and Vierling, K.T., 2015, Establishing conservation baselines with dynamic distribution models for bat populations facing imminent decline: Diversity and Distributions, v. 21, no. 12, p. 1401-1413, https://doi.org/10.1111/ddi.12372.","startPage":"1401","endPage":"1413","numberOfPages":"13","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063534","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":471560,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ddi.12372","text":"Publisher Index Page"},{"id":325981,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon, Washington","volume":"21","issue":"12","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-21","publicationStatus":"PW","scienceBaseUri":"57a1c42fe4b006cb45552c10","contributors":{"authors":[{"text":"Rodhouse, Thomas J.","contributorId":127378,"corporation":false,"usgs":false,"family":"Rodhouse","given":"Thomas J.","affiliations":[{"id":6924,"text":"National Park Service, Upper Columbia Basin Network","active":true,"usgs":false}],"preferred":false,"id":644350,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ormsbee, Patricia C.","contributorId":127379,"corporation":false,"usgs":false,"family":"Ormsbee","given":"Patricia C.","affiliations":[{"id":6925,"text":"US Forest Service, retired","active":true,"usgs":false}],"preferred":false,"id":644351,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Irvine, Kathryn M. 0000-0002-6426-940X kirvine@usgs.gov","orcid":"https://orcid.org/0000-0002-6426-940X","contributorId":2218,"corporation":false,"usgs":true,"family":"Irvine","given":"Kathryn","email":"kirvine@usgs.gov","middleInitial":"M.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":644349,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vierling, Lee A.","contributorId":169443,"corporation":false,"usgs":false,"family":"Vierling","given":"Lee","email":"","middleInitial":"A.","affiliations":[{"id":6711,"text":"University of Idaho, Moscow ID","active":true,"usgs":false}],"preferred":false,"id":644352,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Szewczak, Joseph M.","contributorId":30127,"corporation":false,"usgs":false,"family":"Szewczak","given":"Joseph","email":"","middleInitial":"M.","affiliations":[{"id":6958,"text":"Department of Biological Sciences, Humboldt State University","active":true,"usgs":false}],"preferred":false,"id":644353,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Vierling, Kerri T.","contributorId":140099,"corporation":false,"usgs":false,"family":"Vierling","given":"Kerri","email":"","middleInitial":"T.","affiliations":[{"id":13384,"text":"Department of Fish and Wildlife Sciences, University of Idaho,","active":true,"usgs":false}],"preferred":false,"id":644354,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70159986,"text":"ds975 - 2015 - The U.S. Geological Survey coal quality (COALQUAL) database version 3.0","interactions":[],"lastModifiedDate":"2015-12-21T14:50:46","indexId":"ds975","displayToPublicDate":"2015-12-21T15:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"975","title":"The U.S. Geological Survey coal quality (COALQUAL) database version 3.0","docAbstract":"Since the mid-1970s, the U.S. Geological Survey (USGS) has maintained a coal quality database of national scope named USCHEM, which currently contains data for over 13,000 samples. A subset of the USCHEM database called COALQUAL Version 1.3 was initially published in 1994 and was followed by Version 2.0 in 1997. Version 3.0 of the COALQUAL database represents a major editing effort to resolve some of the DOS software limitations used by earlier versions of the database.
\nBecause of database size limits during the development of COALQUAL Version 1.3, many analyses of individual bench samples were merged into whole coal bed averages. The methodology for making these composite intervals was not consistent. Size limits also restricted the amount of georeferencing information and forced removal of qualifier notations such as \"less than detection limit\" (<) information, which can cause problems when using the data. A review of the original data sheets revealed that COALQUAL Version 2.0 was missing information that was needed for a complete understanding of a coal section. Another important database issue to resolve was the USGS \"remnant moisture\" problem. Prior to 1998, tests for remnant moisture (as-determined moisture in the sample at the time of analysis) were not performed on any USGS major, minor, or trace element coal analyses. Without the remnant moisture, it is impossible to convert the analyses to a usable basis (as-received, dry, etc.). Based on remnant moisture analyses of hundreds of samples of different ranks (and known residual moisture) reported after 1998, it was possible to develop a method to provide reasonable estimates of remnant moisture for older data to make it more useful in COALQUAL Version 3.0. In addition, COALQUAL Version 3.0 is improved by (1) adding qualifiers, including statistical programming to deal with the qualifiers; (2) clarifying the sample compositing problems; and (3) adding associated samples. Version 3.0 of COALQUAL also represents the first attempt to incorporate data verification by mathematically crosschecking certain analytical parameters. Finally, a new database system was designed and implemented to replace the outdated DOS program used in earlier versions of the database.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds975","usgsCitation":"Palmer, C.A., Oman, C.L., Park, A.J., and Luppens, J.A., 2015, The U.S. Geological Survey coal quality (COALQUAL) database version 3.0: U.S. Geological Survey Data Series 975, 43 p. with appendixes, https://dx.doi.org/10.3133/ds975.","productDescription":"Report: v, 50 p.; Database","numberOfPages":"57","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-038492","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":312552,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0975/ds975.pdf","size":"5.95 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 975"},{"id":312553,"rank":3,"type":{"id":9,"text":"Database"},"url":"https://ncrdspublic.er.usgs.gov/coalqual/","text":"COALQUAL Database","description":"DS 975"},{"id":312551,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/0975/coverthb.jpg"}],"contact":"Eastern Energy Resources Science Center
U.S. Geological Survey
Mail Stop 913 National Center
12201 Sunrise Valley Drive
Reston, Virginia 20192
Or visit the USGS Eastern Energy Resources Science Center Web site at:
http://energy.usgs.gov/GeneralInfo/
ScienceCenters/Eastern.aspx
Water use, such as withdrawals, wastewater return flows, and interbasin transfers, can alter streamflow regimes, water quality, and the integrity of aquatic habitat and affect the availability of water for human and ecosystem needs. To provide the information needed to determine alteration of streamflows and pond water levels in southeastern Massachusetts, existing groundwater models of the Plymouth-Carver region and western (Sagamore flow lens) and eastern (Monomoy flow lens) Cape Cod were used to delineate subbasins and simulate long-term average and average monthly streamflows and pond levels for a series of water-use conditions. Model simulations were used to determine the extent to which streamflows and pond levels were altered by comparing simulated streamflows and pond levels under predevelopment conditions with streamflows and pond levels under pumping only and pumping with wastewater return flow conditions. The pumping and wastewater return flow rates used in this study are the same as those used in previously published U.S. Geological Survey studies in southeastern Massachusetts and represent the period from 2000 to 2005. Streamflow alteration for the nontidal portions of streams in southeastern Massachusetts was evaluated within and at the downstream outlets of 78 groundwater subbasins delineated for this study. Evaluation of streamflow alteration at subbasin outlets is consistent with the approach used by the U.S. Geological Survey for the topographically derived subbasins in the rest of Massachusetts.
\nThe net effect of pumping and wastewater return flows on streamflows and pond levels varied by location and included no change in areas minimally affected by water use, decreases in areas affected more by pumping than by wastewater return flows, or increases in areas affected more by wastewater return flows than by pumping. Simulated alterations to long-term average streamflows at subbasin outlets in response to pumping with wastewater return flows were within about 10 percent of predevelopment streamflows for most of the subbasins in the study area. Alterations ranged from a decrease (depletion) of 43.9 percent at an unnamed tributary to Salt Pond in the Plymouth-Carver region to an increase (surcharge) of 18.2 percent at an unnamed tributary to the Centerville River on western Cape Cod. In general, the relative effects of pumping and wastewater return flows typically were larger in the subbasins with low streamflows than in the subbasins with high streamflows, and there were more depleted streamflows than surcharged streamflows. Increases in streamflows in response to wastewater return flows were generally largest in subbasins with a high density of septic systems or a centralized wastewater treatment facility. For average monthly conditions, streamflow alteration results were similar spatially to results for long-term average conditions. However, differences in the extent of alteration by month were observed; percentage streamflow depletions in most subbasins typically were greatest during the low-streamflow months of August and October.
\nThe percentages of the total number of ponds affected by pumping with wastewater return flows under long-term average conditions in the modeled areas were 28 percent for the Plymouth-Carver region, 67 percent for western Cape Cod, and 75 percent for eastern Cape Cod. Pond-level alterations ranged from a decrease of 4.6 feet at Great South Pond in the Plymouth Carver region to an increase of 0.9 feet at Wequaquet Lake in western Cape Cod. The magnitudes of monthly alterations to pond water levels were fairly consistent throughout the year.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155168","collaboration":"Prepared in cooperation with the Massachusetts Department of Environmental Protection","usgsCitation":"Carlson, C.S., Walter, D.A., and Barbaro, J.R., 2015, Simulated responses of streams and ponds to groundwater withdrawals and wastewater return flows in southeastern Massachusetts: U.S. Geological Survey Scientific Investigations Report 2015–5168, 60 p., https://dx.doi.org/10.3133/sir20155168.","productDescription":"Report: vii, 60 p.; 2 Tables; 2 Appendixes","numberOfPages":"72","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-065841","costCenters":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"links":[{"id":312500,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5168/sir20155168_appendix2_gis.zip","text":"Appendix 2 - Shapefiles and spreadsheet files","size":"15.8 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2015-5168"},{"id":312497,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5168/coverthb2.jpg"},{"id":312501,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5168/sir20155168_appendix3_gis.zip","text":"Appendix 3 - Shapefiles and spreadsheet files","size":"3.3 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2015-5168"},{"id":312498,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5168/sir20155168.pdf","text":"Report","size":"8.41 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5168"},{"id":312499,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2015/5168/sir20155168_tables3-4.xlsx","text":"Tables 3-4","size":"52 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2015-5168","linkHelpText":"Table 3. Stream identification, landscape characteristics, and Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Or visit our Web site at:
http://newengland.water.usgs.gov
The Ozark aquifer, within the Ozark Plateaus aquifer system (herein referred to as the “Ozark system”), is the primary groundwater source in the Ozark Plateaus physiographic province (herein referred to as the “Ozark Plateaus”) of Arkansas, Kansas, Missouri, and Oklahoma. Groundwater from the Ozark system has historically been an important part of the water resource base, and groundwater availability is a concern in some areas; dependency on the Ozark aquifer as a water supply has caused evolving, localized issues. The construction of a regional potentiometric-surface map of the Ozark aquifer is needed to aid assessment of current and future groundwater use and availability. The regional potentiometric-surface mapping is part of the U.S. Geological Survey (USGS) Groundwater Resources Program initiative (http://water.usgs.gov/ogw/gwrp/activities/regional.html) and the Ozark system groundwater availability project (http://ar.water.usgs.gov/ozarks), which seeks to quantify current groundwater resources, evaluate changes in these resources over time, and provide the information needed to simulate system response to future human-related and environmental stresses.
The Ozark groundwater availability project objectives include assessing (1) growing demands for groundwater and associated declines in groundwater levels as agricultural, industrial, and public supply pumping increases to address needs; (2) regional climate variability and pumping effects on groundwater and surface-water flow paths; (3) effects of a gradual shift to a greater surface-water dependence in some areas; and (4) shale-gas production requiring groundwater and surface water for hydraulic fracturing. Data compiled and used to construct the regional Ozark aquifer potentiometric surface will aid in the assessment of those objectives.
Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
401 Hardin Road
Little Rock, Arkansas 72211–3528
http://ar.water.usgs.gov/
The U.S. Geological Survey estimated volumes of potential additions to oil and gas reserves for the United States by reserve growth in discovered accumulations. These volumes were derived by using a new methodology developed by the U.S. Geological Survey and reviewed by the American Association of Petroleum Geologists Committee on Resource Evaluation. This methodology was used to assess reserve growth in individual accumulations (reservoirs, groups of reservoirs, or fields). Selected, large, well-studied, conventional accumulations in the United States that are estimated to contribute most to reserve growth were assessed using analysis of geology and engineering practices. Potential additions to oil and gas reserves for large, discovered, conventional accumulations outside of the United States due to reserve growth were assessed using the U.S. accumulations as analogs. Potential oil and gas volumes were assumed to be added to proven plus probable reserves.
\nThe U.S. Geological Survey estimated volumes of technically recoverable, conventional petroleum resources resulting from reserve growth for discovered fields outside the United States that have reported in-place oil and gas volumes of 500 million barrels of oil equivalent or greater. The mean volumes of reserve growth were estimated at 665 billion barrels of crude oil; 1,429 trillion cubic feet of natural gas; and 16 billion barrels of natural gas liquids. These volumes constitute a significant portion of the world’s oil and gas resources and represent the potential future growth of current global reserves over time based on better assessment methodology, new technologies, and greater understanding of reservoirs.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155091","usgsCitation":"Klett, T.R., Cook, T.A., Charpentier, R.R., Tennyson, M.E., and Le, P.A., 2015, U.S. Geological Survey assessment of reserve growth outside of the United States: U.S. Geological Survey Scientific Investigations Report 2015–5091,\n13 p., https://dx.doi.org/10.3133/sir20155091.","productDescription":"iv, 13 p.","numberOfPages":"21","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-059896","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":312051,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5091/coverthb.jpg"},{"id":312052,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5091/sir20155091.pdf","text":"Report","size":"1.29 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5091"}],"country":"United 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U.S. Geological Survey
Box 25046, MS-939
Denver Federal Center
Denver, CO 80225-0046
http://energy.usgs.gov/
Florida panthers are among the world’s most endangered — and elusive — animals. For approximately four decades, scientists have been researching this small population of panthers that inhabit the dense forests and swamps of south Florida. Because of their wide habitat range along with an absence of clear visual features, these animals are difficult to detect and identify. In 2013, however, researchers released a study that used camera trap images collected between 2005 and 2007 to generate the first statistically reliable density estimates for the remaining population of this subspecies.
\nCamera traps — remotely activated cameras with infrared sensors — first gained measurable popularity in wildlife conservation in the early 1990s. Today, they’re used for a variety of activities, from species-specific research to broad-scale inventory or monitoring programs that, in some cases, attempt to detect biodiversity across vast landscapes. As this modern tool continues to evolve, it’s worth examining its uses and benefits for wildlife management and conservation.
","language":"English","publisher":"Wildlife Society","publisherLocation":"Lawrence, KS","usgsCitation":"O’Connell, A.F., 2015, A hidden view of wildlife conservation: How camera traps aid science, research and management: The Wildlife Professional, v. 9, no. 3, p. 56-59.","productDescription":"4 p.","startPage":"56","endPage":"59","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063163","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":312707,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":390185,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://wildlife.org/"}],"volume":"9","issue":"3","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"567922a7e4b0da412f4fb507","contributors":{"authors":[{"text":"O’Connell, Allan F. 0000-0001-7032-7023 aoconnell@usgs.gov","orcid":"https://orcid.org/0000-0001-7032-7023","contributorId":471,"corporation":false,"usgs":true,"family":"O’Connell","given":"Allan","email":"aoconnell@usgs.gov","middleInitial":"F.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":571239,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70159746,"text":"ds971 - 2015 - Quality of surface water in Missouri, water year 2014","interactions":[],"lastModifiedDate":"2016-08-10T11:13:35","indexId":"ds971","displayToPublicDate":"2015-12-18T15:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"971","title":"Quality of surface water in Missouri, water year 2014","docAbstract":"The U.S. Geological Survey, in cooperation with the Missouri Department of Natural Resources, designed and operates a series of monitoring stations on streams and springs throughout Missouri known as the Ambient Water-Quality Monitoring Network. During the 2014 water year (October 1, 2013, through September 30, 2014), data were collected at 74 stations—72 Ambient Water-Quality Monitoring Network stations and 2 U.S. Geological Survey National Stream Quality Assessment Network stations. Dissolved oxygen, specific conductance, water temperature, suspended solids, suspended sediment, Escherichia coli bacteria, fecal coliform bacteria, dissolved nitrate plus nitrite as nitrogen, total phosphorus, dissolved and total recoverable lead and zinc, and select pesticide compound summaries are presented for 71 of these stations. The stations primarily have been classified into groups corresponding to the physiography of the State, primary land use, or unique station types. In addition, a summary of hydrologic conditions in the State including peak discharges, monthly mean discharges, and 7-day low flow is presented.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds971","collaboration":"Prepared in cooperation with the Missouri Department of Natural Resources","usgsCitation":"Barr, M.N., 2015, Quality of surface water in Missouri, water year 2014: U.S. Geological Survey Data Series 971, 22 p., https://dx.doi.org/10.3133/ds971.","productDescription":"vi, 22 p.","numberOfPages":"32","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-068828","costCenters":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"links":[{"id":312548,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/0971/coverthb.jpg"},{"id":312550,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0971/ds971.pdf","text":"Report","size":"2.05 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 971"}],"country":"United States","state":"Missouri","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -95.78979492187499,\n 40.60561205826018\n ],\n [\n -91.77978515625,\n 40.63896734381723\n ],\n [\n -91.56005859375,\n 40.48873742102282\n ],\n [\n -91.4501953125,\n 40.421860362045194\n ],\n [\n -91.51611328125,\n 40.17887331434696\n ],\n [\n -91.461181640625,\n 39.985538414809746\n ],\n [\n -91.417236328125,\n 39.842286020743394\n ],\n [\n -91.285400390625,\n 39.69873414348139\n ],\n [\n -91.01074218749999,\n 39.52099229357195\n ],\n [\n -90.692138671875,\n 39.198205348894795\n ],\n [\n -90.615234375,\n 39.01064750994083\n ],\n [\n -90.54931640625,\n 38.91668153637508\n ],\n [\n -90.439453125,\n 38.95940879245423\n ],\n [\n -90.1318359375,\n 38.89958342598271\n ],\n [\n -90.120849609375,\n 38.8225909761771\n ],\n [\n -90.15380859375,\n 38.659777730712534\n ],\n [\n -90.252685546875,\n 38.47939467327645\n ],\n [\n -90.340576171875,\n 38.315801006824984\n ],\n [\n -90.24169921875,\n 38.1777509666256\n ],\n [\n -90.010986328125,\n 38.048091067457236\n ],\n [\n -89.89013671875,\n 38.004819966413194\n ],\n [\n -89.659423828125,\n 37.84015683604136\n ],\n [\n -89.527587890625,\n 37.71859032558816\n ],\n [\n -89.45068359374999,\n 37.56199695314352\n ],\n [\n -89.45068359374999,\n 37.43125050179356\n ],\n [\n -89.5166015625,\n 37.29153547292737\n ],\n [\n -89.36279296875,\n 37.13404537126446\n ],\n [\n -89.307861328125,\n 37.00255267215955\n ],\n [\n -89.27490234375,\n 37.10776507118514\n ],\n [\n -89.154052734375,\n 37.020098201368114\n ],\n [\n -89.09912109375,\n 36.949891786813296\n ],\n [\n -89.1650390625,\n 36.81808022778526\n ],\n [\n -89.14306640625,\n 36.73888412439431\n ],\n [\n -89.154052734375,\n 36.67723060234619\n ],\n [\n -89.20898437499999,\n 36.58906837139909\n ],\n [\n -89.307861328125,\n 36.615527631349224\n ],\n [\n -89.384765625,\n 36.55377524336086\n ],\n [\n -89.483642578125,\n 36.46547188679816\n ],\n [\n -89.549560546875,\n 36.55377524336086\n ],\n [\n -89.549560546875,\n 36.474306755095206\n ],\n [\n -89.56054687499999,\n 36.31512514748051\n ],\n [\n -89.53857421875,\n 36.26199220445664\n ],\n [\n -89.67041015625,\n 36.2265501474709\n ],\n [\n -89.571533203125,\n 36.182224980422525\n ],\n [\n -89.69238281249999,\n 36.08462129606931\n ],\n [\n -89.703369140625,\n 36.02244668175846\n ],\n [\n -90.3955078125,\n 36.00467348670187\n ],\n [\n -90.32958984375,\n 36.11125252076159\n ],\n [\n -90.186767578125,\n 36.20882309283712\n ],\n [\n -90.087890625,\n 36.30627216957992\n ],\n [\n -90.06591796875,\n 36.37706783983682\n ],\n [\n -90.17578124999999,\n 36.41244153535644\n ],\n [\n -90.186767578125,\n 36.500805317604794\n ],\n [\n -94.625244140625,\n 36.50963615733049\n ],\n [\n -94.625244140625,\n 38.95940879245423\n ],\n [\n -94.68017578125,\n 39.155622393423215\n ],\n [\n -94.866943359375,\n 39.2407625100131\n ],\n [\n -94.888916015625,\n 39.308800296002914\n ],\n [\n -94.921875,\n 39.37677199661635\n ],\n [\n -95.0537109375,\n 39.49556336059472\n ],\n [\n -95.07568359375,\n 39.58029027440865\n ],\n [\n -95.020751953125,\n 39.707186656826565\n ],\n [\n -94.921875,\n 39.757879992021756\n ],\n [\n -94.89990234375,\n 39.825413103424786\n ],\n [\n -94.9658203125,\n 39.90130858574735\n ],\n [\n -95.042724609375,\n 39.884450178234395\n ],\n [\n -95.1416015625,\n 39.884450178234395\n ],\n [\n -95.29541015625,\n 39.9434364619742\n ],\n [\n -95.394287109375,\n 40.01920130768676\n ],\n [\n -95.43823242187499,\n 40.111688665595956\n ],\n [\n -95.482177734375,\n 40.195659093364654\n ],\n [\n -95.526123046875,\n 40.25437660372649\n ],\n [\n -95.657958984375,\n 40.29628651711716\n ],\n [\n -95.64697265625,\n 40.39676430557203\n ],\n [\n -95.723876953125,\n 40.538851525354644\n ],\n [\n -95.78979492187499,\n 40.60561205826018\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Missouri Water Science Center
U.S. Geological Survey
1400 Independence Road
Rolla, MO 65401
http://mo.water.usgs.gov/
In this paper, we present a methodology to use annual tree-ring chronologies and a monthly water balance model to generate annual reconstructions of water balance variables (e.g., potential evapotrans- piration (PET), actual evapotranspiration (AET), snow water equivalent (SWE), soil moisture storage (SMS), and runoff (R)). The method involves resampling monthly temperature and precipitation from the instrumental record directed by variability indicated by the paleoclimate record. The generated time series of monthly temperature and precipitation are subsequently used as inputs to a monthly water balance model. The methodology is applied to the Upper Colorado River Basin, and results indicate that the methodology reliably simulates water-year runoff, maximum snow water equivalent, and seasonal soil moisture storage for the instrumental period. As a final application, the methodology is used to produce time series of PET, AET, SWE, SMS, and R for the 1404–1905 period for the Upper Colorado River Basin.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2015WR017283","usgsCitation":"Gangopadhyay, S., McCabe, G., and Woodhouse, C.A., 2015, Beyond annual streamflow reconstructions for the Upper Colorado River Basin: a paleo-water-balance approach: Water Resources Research, v. 51, no. 12, p. 9763-9774, https://doi.org/10.1002/2015WR017283.","productDescription":"12 p.","startPage":"9763","endPage":"9774","ipdsId":"IP-069011","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":344497,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.0390625,\n 43.14909399920127\n ],\n [\n -110.50048828124999,\n 42.45588764197166\n ],\n [\n -110.80810546875,\n 41.11246878918088\n ],\n [\n -111.0498046875,\n 40.17887331434696\n ],\n [\n -111.86279296875,\n 37.43997405227057\n ],\n [\n -111.6650390625,\n 36.686041276581925\n ],\n [\n -110.56640625,\n 36.421282443649496\n ],\n [\n -109.599609375,\n 36.33282808737917\n ],\n [\n -109.48974609375,\n 35.7286770448517\n ],\n [\n -108.56689453125,\n 35.7286770448517\n ],\n [\n -108.12744140625,\n 35.782170703266075\n ],\n [\n -107.3583984375,\n 36.54494944148322\n ],\n [\n -107.3583984375,\n 37.42252593456307\n ],\n [\n -107.77587890625,\n 37.70120736474139\n ],\n [\n -107.02880859375,\n 38.77121637244273\n ],\n [\n -106.962890625,\n 40.027614437486655\n ],\n [\n -107.46826171874999,\n 40.245991504199026\n ],\n [\n -107.68798828125,\n 40.96330795307353\n ],\n [\n -108.1494140625,\n 41.705728515237524\n ],\n [\n -107.57812499999999,\n 42.06560675405716\n ],\n [\n -108.984375,\n 42.50450285299051\n ],\n [\n -110.0390625,\n 43.14909399920127\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"51","issue":"12","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-18","publicationStatus":"PW","scienceBaseUri":"59819316e4b0e2f5d463b7a3","contributors":{"authors":[{"text":"Gangopadhyay, Subhrendu 0000-0003-3864-8251","orcid":"https://orcid.org/0000-0003-3864-8251","contributorId":173439,"corporation":false,"usgs":false,"family":"Gangopadhyay","given":"Subhrendu","affiliations":[{"id":7183,"text":"U.S. Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":706719,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCabe, Gregory J. 0000-0002-9258-2997 gmccabe@usgs.gov","orcid":"https://orcid.org/0000-0002-9258-2997","contributorId":1453,"corporation":false,"usgs":true,"family":"McCabe","given":"Gregory J.","email":"gmccabe@usgs.gov","affiliations":[{"id":218,"text":"Denver Federal Center","active":false,"usgs":true}],"preferred":false,"id":706718,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Woodhouse, Connie A.","contributorId":187601,"corporation":false,"usgs":false,"family":"Woodhouse","given":"Connie","email":"","middleInitial":"A.","affiliations":[{"id":32413,"text":"University of Arizona, Tucson, AZ, USA, 85721","active":true,"usgs":false}],"preferred":false,"id":706720,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70159624,"text":"ofr20151216 - 2015 - Monitoring of vegetation response to elk population and habitat management in Rocky Mountain National Park, 2008–14","interactions":[],"lastModifiedDate":"2019-12-27T11:07:01","indexId":"ofr20151216","displayToPublicDate":"2015-12-17T16:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1216","title":"Monitoring of vegetation response to elk population and habitat management in Rocky Mountain National Park, 2008–14","docAbstract":"Since 2008, Rocky Mountain National Park in Colorado has been implementing an elk and vegetation management plan with the goal of managing elk populations and their habitats to improve the condition of key vegetation communities on elk winter range. Management actions that have been taken thus far include small reductions in the elk herd through culling of animals and temporary fencing of large areas of willow and aspen habitat to protect them from elk browsing. As part of the park’s elk and vegetation management plan (EVMP), a monitoring program was established to assess effectiveness of management actions in achieving vegetation goals. We collected data to monitor offtake (consumption) of upland herbaceous plants and willow annually from 2008 to 2014 and to assess aspen stand structure and regeneration and willow cover and height in 2013, 5 years after plan implementation. Loss of many willow and a few aspen monitoring sites to a fire in late 2012 complicated data collection and interpretation of results but will provide opportunities to observe habitat recovery following fire and in the presence and absence of elk herbivory, which will offer important insights into the use of prescribed fire as an additional management tool in these habitats.
\nIncreases in the number of small-diameter, tree-sized (stems greater than 2.5 meter height) aspen stems were observed but only inside fences that excluded ungulates. In unfenced areas, stand structure was stagnant, with many medium- and large-diameter (older) stems and no replacement of small-diameter stems. By 2013, aspen saplings (stems less than or equal to 2.5 meter height) were recruiting on 29 percent of sampled sites, an increase from 13 percent of sites at baseline, but this was mainly due to growth inside fences. Upland herbaceous offtake dropped below baseline levels (61 percent) on both core and noncore winter range in 2010–14. Less than 10 percent of the upland areas had intense herbivory (greater than 85 percent offtake), and less than 30 percent of the landscape had offtake greater than 70 percent after 2009. Offtake levels in 2013 and 2014 indicated an increase in grazing pressure on upland sites compared to 2010–12 levels, but this change may have been in response to loss of large patches of both herbaceous and woody forage in Moraine Park following the 2012 Fern Lake Fire. Winter willow offtake remained steady from 2009 to 2014, and although there were no substantial increases in offtake, there were also no consistent declines. Winter-range willow offtake was below the baseline level of 35 percent only in 2013 and 2014. Willow heights have stayed at or above baseline levels of 0.9 meter. Average heights of willow increased compared to baseline measures within fenced habitat on the core winter range and on noncore (all unfenced) winter range. Willow cover increased at least 75 percent compared to baseline within core winter-range fenced areas and roughly 25 percent in noncore winter range. Overall, during the first 5 years of implementation, the EVMP at Rocky Mountain National Park seems to be making steady progress toward the vegetation objectives set out by the EVMP. Habitat fencing has been the most effective means of improving aspen and willow habitat conditions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151216","collaboration":"In cooperation with the National Park Service","usgsCitation":"Zeigenfuss, L.C., and Johnson, T.L., 2015, Monitoring of vegetation response to elk population and habitat management in Rocky Mountain National Park, 2008–14: U.S. Geological Survey Open-File Report 2015–1216, 44 p., https://dx.doi.org/10.3133/ofr20151216.","productDescription":"vi, 44 p.","numberOfPages":"50","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-057139","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":312403,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1216/ofr20151216.pdf","text":"Report","size":"8.17 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1216"},{"id":312401,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1216/coverthb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Rocky Mountain National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.83473205566406,\n 40.23183929314176\n ],\n [\n -105.57106018066406,\n 40.23183929314176\n ],\n [\n -105.57106018066406,\n 40.43440488077008\n ],\n [\n -105.83473205566406,\n 40.43440488077008\n ],\n [\n -105.83473205566406,\n 40.23183929314176\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Fort Collins Science Center
U.S. Geological Survey
2150 Centre Ave., Bldg. C
Fort Collins, CO 80526–8118
http://www.fort.usgs.gov/
This article presents the scientific rationale for an ambitious ICDP drilling project to continuously sample Late Cretaceous to modern sediment in four different sedimentary basins that transect the equatorial Amazon of Brazil, from the Andean foreland to the Atlantic Ocean. The goals of this project are to document the evolution of plant biodiversity in the Amazon forests and to relate biotic diversification to changes in the physical environment, including climate, tectonism, and the surface landscape. These goals require long sedimentary records from each of the major sedimentary basins across the heart of the Brazilian Amazon, which can only be obtained by drilling because of the scarcity of Cenozoic outcrops. The proposed drilling will provide the first long, nearly continuous regional records of the Cenozoic history of the forests, their plant diversity, and the associated changes in climate and environment. It also will address fundamental questions about landscape evolution, including the history of Andean uplift and erosion as recorded in Andean foreland basins and the development of west-to-east hydrologic continuity between the Andes, the Amazon lowlands, and the equatorial Atlantic. Because many modern rivers of the Amazon basin flow along the major axes of the old sedimentary basins, we plan to locate drill sites on the margin of large rivers and to access the targeted drill sites by navigation along these rivers.
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Continuous Slope-Area (CSA) gages were developed by the Arizona Water Science Center to enable the estimation of hydrographs when direct measurements of discharge cannot be made (Smith and others, 2010). CSA gages extend standard U.S. Geological Survey (USGS) methods for determining peak discharges to mid and high flows over a hydrograph computed at regular intervals with indirect measurement methods (Benson and Dalrymple, 1967; Dalrymple and Benson, 1967). CSA gages combine continuous stage records at two or more (typically three or four) cross sections with crosssection surveys and estimates of channel roughness to compute discharge over a range of flows. With standard indirect methods of determining peak discharge, water-surface elevation in the study reach at the peak flow is estimated from surveys of debris associated with the peak-flow water line. With CSA gages, stages are continuously measured at the cross sections, at regular and synchronized intervals (typically 5 minutes) over a flow event, and discharge can be calculated at each interval.
\nCalculation of discharge using indirect methods has been automated with the slope-area computation (SAC) program (Fulford, 1994). SAC is a widely used program within the USGS; it is easily run and displays output in a clear and convenient format, which includes flags that alert the user to shortcomings in the calculation. Use of SAC has been facilitated by SACGUI (Bradley, 2012; SACGUI uses a version of SAC called SAC7), a user interface that directly reads and displays survey data, allows for specification of water-surface slope and channel roughness, writes the input file for SAC7, runs SAC7, and displays SAC7 output.
\ncsa2sac is a program (appendix 1) that repeatedly runs SAC7 using stage data and a SAC7 input template file to compute the discharge at CSA gages. It is written in the C programming language, and is compatible with 64-bit Windows operating systems. The program reads a SAC7 input file and a file containing stage-data time series. It writes a new version of the SAC7 input file with the stage data for one time step, runs SAC7, then extracts computed discharges from the SAC7 output file and collates the discharges and stages to a separate file. It repeats these steps for each time interval in the stage file to produce a discharge time series from the stage data. csa2sac has been tested with two, three, four, and six cross sections and found to operate successfully. By running SAC7, csa2sac maintains consistency and comparability of both discharges calculated from CSA gages and of standard USGS methods for computing discharges indirectly. Brown and Metcalfe (2014) have made available alternative software for producing CSA discharges.
\nIn addition to csa2sac, the SAC7 program is required. It is the same as the original SAC program, except that it is compiled for 64-bit Windows operating systems and has a slightly different command line input. It is available online (http://water.usgs.gov/software/SAC/) as part of the SACGUI installation program. The program name, “SAC7.exe,” is coded into csa2sac, and must not be changed.
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Anyone who spends more than a few days on Cape Cod (the Cape) quickly becomes a coastal geologist, quickly learning the rhythms of daily tides and the seasonal cycles of beaches growing and being swept away by storms; swimmers and surfers track how the breakers appear, and dog-walkers notice the hard-packed sand blanketed overnight by an airy layer that leaves deep labored tracks.
\nCareful observers whose paths wander to the ocean’s edge will observe many of the landforms and coastal processes described in this book and if we have done our job well, the stories told here will seem familiar. Watchful experience brings insights; indeed, this is how scientists and perhaps how artists work, describing patterns that explain and predict. When is the next high tide? What will the winter bring? Where do we build, fish, swim? How do wind and waves offshore in the North Atlantic help arrange the plants and dunes and hollows on the beach? And most of all, as human animals drawn to live and play on the edge of the ocean, how do we get the benefits of this complex natural system of geology and biology? How do we affect coastal processes; how is the coast changing now and how is the coast likely to change in years ahead with climate warming and climate change?
\nThis book is about the highly dynamic coastal landforms of Cape Cod—the beaches, bluffs, spits, dunes, barrier beaches, estuaries, and salt marshes. What they are, why they are where they are, how they behave with respect to the greater Cape Cod coastal system—how the landforms respond to day-to-day and long-term geologic processes, such as waves and currents, change in sediment transport, relative sea-level rise, and meteorological processes such as hurricanes, nor’easters, and cold front passages. It is also about how the landforms got to be where they are and the way they are and where they are headed in the near future with the predicted effects of global climate warming and change.
\nOur objective is to provide a single source of understandable and readable scientific information for those who live, play, and work on outer Cape Cod and at the Cape Cod National Seashore, as well as to provide an introduction to Cape Cod’s coastal landforms for anyone with an interest in Earth science and nature who wants a better understanding of coastal systems and processes. Basic to an understanding of coastal landforms is the fact that they work together—they interact—as elements of many systems, and therefore our ultimate concern is not the individual landform itself but rather the geologic systems that make up Cape Cod and the Cape Cod National Seashore. Much of this discussion can be applied as well to Nantucket, Martha’s Vineyard, and other coastal regions.
\nThe coast of outer Cape Cod, about 15,000 years old and about 30 miles (mi; 50 kilometers [km]) long, is but a tiny piece of the global Earth system that operates within a much larger realm of space and time. Cape Cod’s coastal landforms are temporary holding patterns within a continual interplay of land, sea, atmosphere, climate, ice, and life, including a variety of human activities that both affect and are affected by these processes. These interactions produce the landforms, and the landforms alter the interactions. The resulting landforms provide habitats for a wide variety of coastal plants and animals. The habitats along with their inhabitants and the interacting environmental factors controlling them constitute the Cape’s complex and varied ecosystems. But for now, we are here to enjoy it. We welcome you to delight and wonder at the perpetually changing handshake between the ocean and shore at New England’s Great Beach.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1417","isbn":"978-1-4113-3994-1","usgsCitation":"Giese, G.S., Williams, S.J., and Adams, Mark, 2015, Coastal landforms and processes at the Cape Cod National Seashore, Massachusetts—A primer: U.S. Geological Survey Circular 1417, 86 p., https://dx.doi.org/10.3133/cir1417.","productDescription":"iv, 86 p.","numberOfPages":"94","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062012","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":503655,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_103782.htm","linkFileType":{"id":5,"text":"html"}},{"id":311914,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1417/circ1417.pdf","text":"Report","size":"4.36 MB","linkFileType":{"id":1,"text":"pdf"},"description":"CIRC 1417"},{"id":311913,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/circ/1417/coverthb.jpg"}],"country":"United States","state":"Massachusetts","otherGeospatial":"Cape Cod National Seashore","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -70.19027709960938,\n 42.014611228817955\n ],\n [\n -70.25550842285156,\n 42.06560675405716\n ],\n [\n -70.22598266601562,\n 42.08038780095535\n ],\n [\n -70.19371032714844,\n 42.08344551881909\n ],\n [\n -70.15731811523438,\n 42.07885888676642\n ],\n [\n -70.08522033691405,\n 42.05897965014623\n ],\n [\n -70.02410888671875,\n 42.00950942549379\n ],\n [\n -69.96986389160156,\n 41.91607416876307\n ],\n [\n -69.94445800781249,\n 41.83733944214672\n ],\n [\n -69.93415832519531,\n 41.78052894057897\n ],\n [\n -69.92729187011719,\n 41.74160260664948\n ],\n [\n -69.92935180664061,\n 41.693936942282164\n ],\n [\n -69.93690490722655,\n 41.66778269875831\n ],\n [\n -69.94720458984375,\n 41.678040531771785\n ],\n [\n -69.93827819824219,\n 41.75184866809371\n ],\n [\n -69.94857788085938,\n 41.83887416186901\n ],\n [\n -69.96780395507811,\n 41.830176930139835\n ],\n [\n -69.98908996582031,\n 41.91454130182335\n ],\n [\n -70.02273559570311,\n 41.96051129429777\n ],\n [\n -70.04539489746094,\n 41.95540515378059\n ],\n [\n -70.04676818847656,\n 41.92833577889557\n ],\n [\n -70.07080078125,\n 41.89409955811395\n ],\n [\n -70.08316040039062,\n 41.95489451722692\n ],\n [\n -70.06393432617188,\n 41.98909812021334\n ],\n [\n -70.04676818847656,\n 42.00287646941049\n ],\n [\n -70.081787109375,\n 42.032464317845175\n ],\n [\n -70.12298583984375,\n 42.05031239367961\n ],\n [\n -70.14770507812499,\n 42.06050904321049\n ],\n [\n -70.16624450683594,\n 42.03144427637554\n ],\n [\n -70.19027709960938,\n 42.014611228817955\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Woods Hole Coastal and Marine Science Center
U.S. Geological Survey
384 Woods Hole Road
Quissett Campus
Woods Hole, MA 0254
http:/woodshole.er.usgs.gov/
The U.S. Geological Survey has a long history of responding to and documenting the impacts of storms along the Nation’s coasts and incorporating these data into storm impact and coastal change vulnerability assessments. These studies, however, have traditionally focused on sandy shorelines and sandy barrier-island systems, without consideration of impacts to coastal wetlands. The goal of the Barrier Island and Estuarine Wetland Physical Change Assessment project is to integrate a wetland-change assessment with existing coastal-change assessments for the adjacent sandy dunes and beaches, initially focusing on Assateague Island along the Maryland and Virginia coastline. Assateague Island was impacted by waves and storm surge associated with the passage of Hurricane Sandy in October 2012, including erosion and overwash along the ocean-facing sandy shoreline as well as erosion and overwash deposition in the back-barrier and estuarine bay environments.
\nThis report serves as an archive of data that were derived from Landsat 5 and Landsat 8 imagery from 1984 to 2014, including wetland and terrestrial habitat extents; open-ocean, back-barrier, and estuarine mainland shoreline positions; and sand-line positions along the estuarine mainland and barrier shorelines from Assateague Island, Maryland to Metompkin Island, Virginia. The geographic information system data files with accompanying formal Federal Geographic Data Committee metadata can be downloaded from the Data Downloads page.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds968","usgsCitation":"Bernier, J.C., Douglas, S.H., Terrano, J.F., Barras, J.A., Plant, N.G., and Smith, C.G., 2015, Land-cover types, shoreline positions, and sand extents derived from Landsat satellite imagery, Assateague Island to Metompkin Island, Maryland and Virginia, 1984 to 2014: U.S. Geological Survey Data Series 968, https://dx.doi.org/10.3133/ds968.","productDescription":"HTML Document","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"1984-01-01","temporalEnd":"2014-12-31","ipdsId":"IP-065873","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":312270,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0968/index.html","text":"Report (HTML format)","description":"DS 968"},{"id":312269,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/0968/images/coverthb.jpg"}],"country":"United States","state":"Maryland, Virginia","otherGeospatial":"Assateague Island, Metompkin Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.10528564453125,\n 38.33303882235456\n ],\n [\n -75.25360107421875,\n 38.23925875585244\n ],\n [\n -75.5474853515625,\n 37.8065289741725\n ],\n [\n -75.30990600585938,\n 37.801103690609615\n ],\n [\n -75.02975463867188,\n 38.33088431959968\n ],\n [\n -75.10528564453125,\n 38.33303882235456\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701
http://coastal.er.usgs.gov/
Wild waterfowl are primary reservoirs of avian influenza viruses (AIV). However the role of sea ducks in the ecology of avian influenza, and how that role differs from freshwater ducks, has not been examined. We obtained and analyzed sera from North Atlantic sea ducks and determined the seroprevalence in those populations. We also tested swab samples from North Atlantic sea ducks for the presence of AIV. We found relatively high serological prevalence (61%) in these sea duck populations but low virus prevalence (0.3%). Using these data we estimated that an antibody half-life of 141 weeks (3.2 years) would be required to attain these prevalences. These findings are much different than what is known in freshwater waterfowl and have implications for surveillance efforts, AIV in marine environments, and the roles of sea ducks and other long-lived waterfowl in avian influenza ecology.
","language":"English","publisher":"Public Library of Science","publisherLocation":"San Francisco, CA","doi":"10.1371/journal.pone.0144524","usgsCitation":"Hall, J.S., Russell, R.E., Franson, J., Soos, C., Dusek, R.J., Allen, R.B., Nashold, S.W., Teslaa, J.L., Jonsson, J.E., Ballard, J.R., Harms, N.J., and Brown, J.D., 2015, Avian influenza ecology in North Atlantic sea ducks: Not all ducks are created equal: PLoS ONE, v. 10, no. 12, p. 1-16, https://doi.org/10.1371/journal.pone.0144524.","productDescription":"16 p.","startPage":"1","endPage":"16","numberOfPages":"16","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069941","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":471563,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0144524","text":"Publisher Index Page"},{"id":316723,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","issue":"12","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-17","publicationStatus":"PW","scienceBaseUri":"56bb1bbce4b08d617f654de1","contributors":{"authors":[{"text":"Hall, Jeffrey S. 0000-0001-5599-2826 jshall@usgs.gov","orcid":"https://orcid.org/0000-0001-5599-2826","contributorId":2254,"corporation":false,"usgs":true,"family":"Hall","given":"Jeffrey","email":"jshall@usgs.gov","middleInitial":"S.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":597668,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Russell, Robin E. 0000-0001-8726-7303 rerussell@usgs.gov","orcid":"https://orcid.org/0000-0001-8726-7303","contributorId":3998,"corporation":false,"usgs":true,"family":"Russell","given":"Robin","email":"rerussell@usgs.gov","middleInitial":"E.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":597669,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Franson, J. Christian jfranson@usgs.gov","contributorId":149318,"corporation":false,"usgs":true,"family":"Franson","given":"J. Christian","email":"jfranson@usgs.gov","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":false,"id":597670,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Soos, Catherine","contributorId":99042,"corporation":false,"usgs":true,"family":"Soos","given":"Catherine","affiliations":[],"preferred":false,"id":597674,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dusek, Robert J. 0000-0001-6177-7479 rdusek@usgs.gov","orcid":"https://orcid.org/0000-0001-6177-7479","contributorId":152316,"corporation":false,"usgs":true,"family":"Dusek","given":"Robert","email":"rdusek@usgs.gov","middleInitial":"J.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":false,"id":597671,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Allen, R. Bradford","contributorId":156366,"corporation":false,"usgs":false,"family":"Allen","given":"R.","email":"","middleInitial":"Bradford","affiliations":[{"id":20327,"text":"Maine Department of Inland Fisheries and Wildlife, Bangor, ME 04401","active":true,"usgs":false}],"preferred":false,"id":597675,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Nashold, Sean W. 0000-0002-8869-6633 snashold@usgs.gov","orcid":"https://orcid.org/0000-0002-8869-6633","contributorId":3611,"corporation":false,"usgs":true,"family":"Nashold","given":"Sean","email":"snashold@usgs.gov","middleInitial":"W.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":false,"id":597672,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Teslaa, Joshua L. 0000-0001-7802-3454 jteslaa@usgs.gov","orcid":"https://orcid.org/0000-0001-7802-3454","contributorId":5794,"corporation":false,"usgs":true,"family":"Teslaa","given":"Joshua","email":"jteslaa@usgs.gov","middleInitial":"L.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":false,"id":597673,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Jonsson, Jon Einar","contributorId":156367,"corporation":false,"usgs":false,"family":"Jonsson","given":"Jon","email":"","middleInitial":"Einar","affiliations":[{"id":20328,"text":"University of Iceland, Snæfellsnes Research Centre, Stykkishólmur, Iceland 245.","active":true,"usgs":false}],"preferred":false,"id":597676,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Ballard, Jennifer R.","contributorId":127726,"corporation":false,"usgs":false,"family":"Ballard","given":"Jennifer","email":"","middleInitial":"R.","affiliations":[{"id":7125,"text":"Southeastern Cooperative Wildlife Disease Study, College of Veterinary Medicine, University of Georgia, Athens, GA 30602, USA.","active":true,"usgs":false}],"preferred":false,"id":597677,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Harms, Naomi Jnae","contributorId":156368,"corporation":false,"usgs":false,"family":"Harms","given":"Naomi","email":"","middleInitial":"Jnae","affiliations":[{"id":20329,"text":"Department of Veterinary Pathology, Western College of Veterinary Medicine,University of","active":true,"usgs":false}],"preferred":false,"id":597678,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Brown, Justin D.","contributorId":87838,"corporation":false,"usgs":false,"family":"Brown","given":"Justin","email":"","middleInitial":"D.","affiliations":[{"id":7125,"text":"Southeastern Cooperative Wildlife Disease Study, College of Veterinary Medicine, University of Georgia, Athens, GA 30602, USA.","active":true,"usgs":false}],"preferred":false,"id":597679,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70159548,"text":"fs20153078 - 2015 - Assessment of undiscovered shale gas and shale oil resources in the Mississippian Barnett Shale, Bend Arch–Fort Worth Basin Province, North-Central Texas","interactions":[],"lastModifiedDate":"2018-02-15T15:02:56","indexId":"fs20153078","displayToPublicDate":"2015-12-17T10:35:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-3078","title":"Assessment of undiscovered shale gas and shale oil resources in the Mississippian Barnett Shale, Bend Arch–Fort Worth Basin Province, North-Central Texas","docAbstract":"Using a geology-based assessment methodology, the U.S. Geological Survey estimated mean volumes of 53 trillion cubic feet of shale gas, 172 million barrels of shale oil, and 176 million barrels of natural gas liquids in the Barnett Shale of the Bend Arch–Fort Worth Basin Province of Texas.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20153078","usgsCitation":"Marra, K.R., Charpentier, R.R., Schenk, C.J., Lewan, M.D., Leathers-Miller, H.M., Klett, T.R., Gaswirth, S.B., Le, P.A., Mercier, T.J., Pitman, J.K., and Tennyson, M.E., 2015, Assessment of undiscovered shale gas and shale oil resources in the Mississippian Barnett Shale, Bend Arch–Fort Worth Basin Province, north-central Texas: U.S. Geological Survey Fact Sheet 2015-3078, 2 p., https://dx.doi.org/10.3133/fs20153078.","productDescription":"2 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069192","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":312038,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2015/3078/coverthb.jpg"},{"id":312039,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2015/3078/fs20153078.pdf"},{"id":349490,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20175102","text":"Scientific Investigations Report 2017-5102","linkHelpText":"Procedure for Calculating Estimated Ultimate Recoveries of Wells in the Mississippian Barnett Shale, Bend Arch–Fort Worth Basin Province of North-Central Texas"}],"country":"United States","state":"Texas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -102.37060546875,\n 29.017748018496047\n ],\n [\n -102.37060546875,\n 35.33529320309331\n ],\n [\n -94.4384765625,\n 35.33529320309331\n ],\n [\n -94.4384765625,\n 29.017748018496047\n ],\n [\n -102.37060546875,\n 29.017748018496047\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver Federal Center
Denver, CO 80225-0046
http://energy.usgs.gov/
American Bullfrogs (Lithobates catesbeianus) have been introduced across the globe, including in many northern latitude habitats where wetlands are ice-covered for part of the year. Because bullfrogs are less mobile at low temperatures, greater knowledge about their overwintering habitat may provide additional opportunities for control. Here, we described fall and early-winter movements and habitat associations for introduced juvenile bullfrogs in a pond within the Yellowstone River corridor near Billings, Montana, USA. We attached radio-transmitters to 13 juvenile bullfrogs and located individuals from 28 August to 10 December 2014. Bullfrogs moved greater distances in late summer and early autumn, and later during brief warming periods. Collectively, all bullfrog locations were distributed across a 15,384 m2 area during the active season, but contracted to a 130 m2 area in the east cove of the pond by the time the study site froze over. Our research provides evidence that managers in northern latitude regions like Montana may be able to use the long, cold winters to their advantage because the site-specific distributions of introduced bullfrogs contracted as temperatures decreased.
","language":"English","usgsCitation":"Sepulveda, A.J., and Layhee, M.J., 2015, Fall and winter movements and habitat use of the introduced American bullfrog (Lithobates catesbeiana) in a Montana pond: Herpetological Conservation and Biology, v. 10, no. 3, p. 978-984.","productDescription":"7 p.","startPage":"978","endPage":"984","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066117","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":312429,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":312428,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.herpconbio.org/Volume_10/Issue_3/"}],"country":"United States","state":"Montana","city":"Billings","otherGeospatial":"Will's Marsh","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.78387451171875,\n 45.644768217751924\n ],\n [\n -108.78387451171875,\n 45.89956596377031\n ],\n [\n -108.314208984375,\n 45.89956596377031\n ],\n [\n -108.314208984375,\n 45.644768217751924\n ],\n [\n -108.78387451171875,\n 45.644768217751924\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5673dcb1e4b0da412f4f81f7","contributors":{"authors":[{"text":"Sepulveda, Adam J. 0000-0001-7621-7028 asepulveda@usgs.gov","orcid":"https://orcid.org/0000-0001-7621-7028","contributorId":150628,"corporation":false,"usgs":true,"family":"Sepulveda","given":"Adam","email":"asepulveda@usgs.gov","middleInitial":"J.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":582478,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Layhee, Megan J. 0000-0003-1359-1455 mlayhee@usgs.gov","orcid":"https://orcid.org/0000-0003-1359-1455","contributorId":3955,"corporation":false,"usgs":true,"family":"Layhee","given":"Megan","email":"mlayhee@usgs.gov","middleInitial":"J.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":582479,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70159489,"text":"ofr20151188B - 2015 - Standard operating procedures for collection of soil and sediment samples for the Sediment-bound Contaminant Resiliency and Response (SCoRR) strategy pilot study","interactions":[],"lastModifiedDate":"2016-08-26T09:43:25","indexId":"ofr20151188B","displayToPublicDate":"2015-12-17T10:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1188","chapter":"B","title":"Standard operating procedures for collection of soil and sediment samples for the Sediment-bound Contaminant Resiliency and Response (SCoRR) strategy pilot study","docAbstract":"An understanding of the effects on human and ecological health brought by major coastal storms or flooding events is typically limited because of a lack of regionally consistent baseline and trends data in locations proximal to potential contaminant sources and mitigation activities, sensitive ecosystems, and recreational facilities where exposures are probable. In an attempt to close this gap, the U.S. Geological Survey (USGS) has implemented the Sediment-bound Contaminant Resiliency and Response (SCoRR) strategy pilot study to collect regional sediment-quality data prior to and in response to future coastal storms. The standard operating procedure (SOP) detailed in this document serves as the sample-collection protocol for the SCoRR strategy by providing step-by-step instructions for site preparation, sample collection and processing, and shipping of soil and surficial sediment (for example, bed sediment, marsh sediment, or beach material). The objectives of the SCoRR strategy pilot study are (1) to create a baseline of soil-, sand-, marsh sediment-, and bed-sediment-quality data from sites located in the coastal counties from Maine to Virginia based on their potential risk of being contaminated in the event of a major coastal storm or flooding (defined as Resiliency mode); and (2) respond to major coastal storms and flooding by reoccupying select baseline sites and sampling within days of the event (defined as Response mode). For both modes, samples are collected in a consistent manner to minimize bias and maximize quality control by ensuring that all sampling personnel across the region collect, document, and process soil and sediment samples following the procedures outlined in this SOP. Samples are analyzed using four USGS-developed screening methods—inorganic geochemistry, organic geochemistry, pathogens, and biological assays—which are also outlined in this SOP. Because the SCoRR strategy employs a multi-metric approach for sample analyses, this protocol expands upon and reconciles differences in the sample collection protocols outlined in the USGS “National Field Manual for the Collection of Water-Quality Data,” which should be used in conjunction with this SOP. A new data entry and sample tracking system also is presented to ensure all relevant data and metadata are gathered at the sample locations and in the laboratories.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151188B","collaboration":"Toxic Substances Hydrology Program","usgsCitation":"Fisher, S.C., Reilly, T.J., Jones, D.K., Benzel, W.M., Griffin, D.W., Loftin, K.A., Iwanowicz, L.R., and Cohl, J.A., 2015, Standard operating procedure for collection of soil and sediment samples for the Sediment-bound Contaminant Resiliency and Response (SCoRR) strategy pilot study: U.S. Geological Survey Open-File Report 2015–1188b, 37 p., https://dx.doi.org/10.3133/ofr20151188B.","productDescription":"v, 37 p.","numberOfPages":"48","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-066316","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":312385,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/ofr20151188A","text":"Open-File Report 2015-1188A","description":"OFR 2015-1188B","linkHelpText":"Strategy to Evaluate Persistent Contaminant Hazards Resulting from Sea-Level RiseToxic Substances Hydrology Program
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, Virginia 20192
http://www.usgs.gov/envirohealth/
http://health.usgs.gov/scorr/